Speaker:  Hoon Cho (Yale University)

Title: Computational solutions for privacy challenges in biomedicine

Abstract: The sensitive nature of biomedical data presents significant challenges for data sharing. Traditional safeguards, such as access controls and privacy regulations, have resulted in the fragmentation of biomedical data across silos. In this talk, I will demonstrate the crucial role mathematical techniques play in overcoming privacy challenges in biomedicine. I will first describe how joint probabilistic modeling of genomic and transcriptomic data can improve our understanding of privacy risks. Following this, I will discuss how our novel algorithm design, which integrates ideas from cryptography, distributed optimization, and statistical genetics, has led to a suite of secure federated (SF) tools. These tools facilitate large-scale, privacy-preserving joint analysis of biomedical data across silos. Finally, I will share our recent efforts to deploy these tools across biobanks and discuss future research directions.

Bio: Hyunghoon (Hoon) Cho, PhD, is an Assistant Professor of Biomedical Informatics and Data Science at Yale University. Previously, he was a Schmidt Fellow and Principal Investigator at the Broad Institute of MIT and Harvard. He received his Ph.D. in Electrical Engineering and Computer Science at MIT in 2019 and previously obtained both an M.S. and a B.S. with Honors in Computer Science from Stanford University. He has been named a recipient of the NIH Director's Early Independence Award.